Robots have been deployed across numerous industrial and manufacturing environments to promote reliability and cost savings. For example, a robotic arm can move objects to perform tasks, including assembly, packaging, inspection, etc. Conventional industrial robots are generally quite stiff, fast, and precise; these characteristics, particularly speed and stiffness, may cause danger to human workers. As a result, conventional industrial robots are typically separated from human workers by, for example, cages, barriers or sensors that can detect the presence of human workers. The separation poses challenges for training the robots, often requiring non-intuitive training sequences carried out at a distance.
Recently, a new class of robots that can work collaboratively with human workers has been developed. These collaborative robots are generally more compliant, contain integral sensing, and move at speeds designed not to pose a hazard to nearby human workers. These collaborative robots are also easier to program because a human worker may be able to teach a task by directly manipulating the robots. However, the same characteristics, i.e., compliance and safe speeds, often compromise the ability to perform a manipulative task; performance metrics such as speed and/or precision generally favor conventional robots.
While it may be possible to utilize both types of robot on a single manufacturing floor (e.g., by partitioning floor space so that the conventional robots cannot come into contact with humans), the practicalities of implementing a working “hybrid” line involving conventional and collaborative robots are considerable. While collaborative robots are expressly designed for easy training by an operator, conventional robots must be trained separately and, as noted above, using more cumbersome techniques. Until this barrier to effective combined use of collaborative and conventional robots is overcome, the ability to use them in a hybrid configuration will remain limited, and the difficulty of training conventional robots will remain.